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Computational Intelligence Techniques in Medical Decision Making: the Data Mining Perspective

  • V. Maojo
  • J. Sanandres
  • H. Billhardt
  • J. Crespo
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 96)

Abstract

In this chapter, we give an overview of computational approaches to medical decision making, with particular emphasis on data mining methods. Medicine has been one of the most challenging application areas for Artificial Intelligence since the 1970s. The first generation of expert systems was an academic success. However, these systems failed to have a clinical impact. Researchers realized that medicine, and particularly patient care, is a complex domain, where requirements are different from other areas. A host of approaches were later adopted, including extracting objective information and knowledge from institutional and clinical databases using data mining. We give an overview of data mining methods, including neural networks, fuzzy sets and other machine learning approaches. Several examples of practical medical applications are presented. Finally, we discuss several limitations that must be overcome to effectively apply data mining methods and results to patient care.

Keywords

Data Mining Medical Decision Radial Basis Function Network Electronic Patient Record Medical Informatics 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • V. Maojo
  • J. Sanandres
  • H. Billhardt
  • J. Crespo

There are no affiliations available

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